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如何高性能计算出一个列表相近 3 个数据的最大值和最小值?
举例：如下列表临近 3 个数据的最大值和最小值 [1,2,3,4,5,7,8,9,10] 输出 最大值为：27 最小值为：6
 | 1 hongch Mar 23, 2021 题目应该指明是无序数组吧？ |
 | 2 hehe12980 Mar 23, 2021 随便给你写了一个 def arr = [1, 2, 3, 4, 5, 7, 8, 9, 10] if (arr.size() < 3) { return } int min = arr[0] + arr[1] + arr[2] int max = arr[0] + arr[1] + arr[2] int prefix = 0 for (int i = 3; i < arr.size(); i++) { int sum = arr[i] + max - arr[prefix++] max = Math.max(max, sum) min = Math.min(max, min) } println(min) println(max) |
| 3 hehe12980 Mar 23, 2021 @hehe12980 上面好像写的不太对 def arr = [1, 2, 3, 4, 5, 7, 8, 9, 10] if (arr.size() < 3) { return } int min = arr[0] + arr[1] + arr[2] int max = arr[0] + arr[1] + arr[2] int prefix = 0 for (int i = 3; i < arr.size(); i++) { int sum = arr[i] + max - arr[prefix++] max = Math.max(max, sum) min = Math.min(min, sum) } println(min) println(max) |
 | 4 ClutchBear Mar 23, 2021  1 单纯的 o(n)啊 计算每个元素和后面两个元素的和. 然后比较 |
| 5 ClutchBear Mar 23, 2021 data = [1, 2, 3, 4, 5, 7, 8, 9, 10] max_sum = data[0] + data[1] + data[2] min_sum = max_sum temp_list = [] data_length = len(data) for index, item in enumerate(data): if data_length == index + 2: break temp_list = [item, data[index + 1], data[index + 2]] temp_list_sum = sum(temp_list) if temp_list_sum > max_sum: max_sum = temp_list_sum if temp_list_sum < min_sum: min_sum = temp_list_sum print(max_sum, min_sum) |
 | 6 BBrother Mar 23, 2021 1 数组顺序不能改的话用滑动窗口 |
 | 7 zyb201314 Mar 23, 2021 via Android #这咋样? import heapq s=[9,2,3,6,10,5,7,1,8] print(sum(heapq.nsmallest(3,s))) print(sum(heapq.nlargest(3,s))) |
 | 8 Vegetable Mar 23, 2021 这和遍历一遍找出极值没什么区别吧 |
 | 11 todd7zhang Mar 24, 2021 老老实实遍历就完事，O(n) |
 | 12 princelai Mar 24, 2021 高性能用 numpy 啊，你要是刷题没法引入外部包那就没办法了 ``` import numpy as np w=3 arr = np.array([1,2,3,4,5,7,8,9,10]) x,y = np.ogrid[:arr.shape[0]-w+1,:w] rolling_sum = arr[x+y].sum(axis=1) # 上两步替代方法 # np.lib.stride_tricks.sliding_window_view(arr,w).sum(axis=1) print(f"最小值：{rolling_sum.min()}\t 最大值{rolling_sum.max()}") ``` |
 | 13 Pagliacii Mar 24, 2021 |
 | 14 livrth Mar 24, 2021 via Android 单调队列 滑动窗口 O （ N ） |
 | 15 adocder Apr 21, 2021 应该是考察排序吧 |
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